import streamlit as st
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
from datetime import datetime, timedelta
from app.services.extruder_service import ExtruderService
from app.services.data_processing_service import DataProcessingService

def show_extruder_dashboard():
    # 初始化服务
    extruder_service = ExtruderService()
    processing_service = DataProcessingService()

    # 页面标题
    st.title("挤出机数据分析")

    # 初始化会话状态用于日期同步
    if 'extruder_start_date' not in st.session_state:
        st.session_state['extruder_start_date'] = datetime.now().date() - timedelta(days=7)
    if 'extruder_end_date' not in st.session_state:
        st.session_state['extruder_end_date'] = datetime.now().date()
    if 'extruder_quick_select' not in st.session_state:
        st.session_state['extruder_quick_select'] = "最近7天"

    # 定义回调函数
    def update_dates(qs):
        st.session_state['extruder_quick_select'] = qs
        today = datetime.now().date()
        if qs == "今天":
            st.session_state['extruder_start_date'] = today
            st.session_state['extruder_end_date'] = today
        elif qs == "最近3天":
            st.session_state['extruder_start_date'] = today - timedelta(days=3)
            st.session_state['extruder_end_date'] = today
        elif qs == "最近7天":
            st.session_state['extruder_start_date'] = today - timedelta(days=7)
            st.session_state['extruder_end_date'] = today
        elif qs == "最近30天":
            st.session_state['extruder_start_date'] = today - timedelta(days=30)
            st.session_state['extruder_end_date'] = today

    def on_date_change():
        st.session_state['extruder_quick_select'] = "自定义"

    # 查询条件区域
    with st.expander("🔍 查询配置", expanded=True):
        # 添加自定义 CSS 实现响应式换行
        st.markdown("""
            <style>
            /* 强制列容器换行 */
            [data-testid="stExpander"] [data-testid="column"] {
                flex: 1 1 120px !important;
                min-width: 120px !important;
            }
            /* 针对日期输入框列稍微加宽一点 */
            @media (min-width: 768px) {
                [data-testid="stExpander"] [data-testid="column"]:nth-child(6),
                [data-testid="stExpander"] [data-testid="column"]:nth-child(7) {
                    flex: 2 1 180px !important;
                    min-width: 180px !important;
                }
            }
            </style>
            """, unsafe_allow_html=True)
            
        # 创建布局
        cols = st.columns([1, 1, 1, 1, 1, 1.5, 1.5, 1])
        
        options = ["今天", "最近3天", "最近7天", "最近30天", "自定义"]
        for i, option in enumerate(options):
            with cols[i]:
                # 根据当前选择状态决定按钮类型
                button_type = "primary" if st.session_state['extruder_quick_select'] == option else "secondary"
                if st.button(option, key=f"btn_extruder_{option}", width='stretch', type=button_type):
                    update_dates(option)
                    st.rerun()

        with cols[5]:
            start_date = st.date_input(
                "开始日期", 
                label_visibility="collapsed",
                key="extruder_start_date",
                on_change=on_date_change
            )
        
        with cols[6]:
            end_date = st.date_input(
                "结束日期", 
                label_visibility="collapsed",
                key="extruder_end_date",
                on_change=on_date_change
            )

        with cols[7]:
            query_button = st.button("🚀 查询", key="extruder_query", width='stretch')

    # 转换为datetime对象（包含时间）
    start_datetime = datetime.combine(start_date, datetime.min.time())
    end_datetime = datetime.combine(end_date, datetime.max.time())

    # 查询按钮处理
    if query_button:
        # 验证日期范围
        if start_datetime > end_datetime:
            st.error("开始日期不能晚于结束日期！")
        else:
            # 显示加载状态
            with st.spinner("正在查询数据..."):
                # 查询数据
                raw_data = extruder_service.get_extruder_data(start_datetime, end_datetime)
                
                if raw_data is None or raw_data.empty:
                    st.warning("未查询到数据，请检查日期范围或数据库连接！")
                    st.session_state['extruder_results'] = None
                else:
                    # 清洗数据
                    cleaned_data = processing_service.clean_data(raw_data)
                    
                    # 检测换批事件
                    batch_changes = extruder_service.detect_batch_changes(cleaned_data)
                    
                    # 缓存结果
                    st.session_state['extruder_results'] = {
                        'cleaned_data': cleaned_data,
                        'batch_changes': batch_changes,
                    }
                    
                    # 显示数据概览
                    st.subheader("数据概览")
                    col1, col2, col3, col4 = st.columns(4)
                    
                    with col1:
                        st.metric("总记录数", len(cleaned_data))
                    
                    with col2:
                        st.metric("换批次数", len(batch_changes))
                    
                    with col3:
                        st.metric("数据时间范围", f"{cleaned_data['time'].min()} 至 {cleaned_data['time'].max()}")
                    
                    # 显示换批分析
                    st.subheader("换批分析")
                    if not batch_changes.empty:
                        # 准备展示数据
                        batch_display = batch_changes[['batch_id', 'compound_code', 'start_time', 'end_time', 'duration_minutes']].copy()
                        
                        # 格式化时间
                        batch_display['start_time'] = batch_display['start_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
                        batch_display['end_time'] = batch_display['end_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
                        
                        # 修改列名
                        batch_display.columns = ['批号', '胶料号', '开始时间', '结束时间', '持续时长(分钟)']                                
                        # 显示数据表格
                        st.dataframe(batch_display, use_container_width=True)
                    else:
                        st.warning("未检测到换批事件")
                    
                    # 显示换料操作可视化图表
                    st.subheader("换料操作可视化")
                    if not batch_changes.empty:
                        # 创建换料操作可视化图表
                        fig = go.Figure()
                        
                        # 添加关键参数趋势线
                        fig.add_trace(go.Scatter(
                            x=cleaned_data['time'],
                            y=cleaned_data['screw_speed_actual'],
                            name='实际转速',
                            line=dict(color='blue', width=2),
                            opacity=0.8
                        ))
                        
                        fig.add_trace(go.Scatter(
                            x=cleaned_data['time'],
                            y=cleaned_data['head_pressure'],
                            name='机头压力',
                            line=dict(color='red', width=2),
                            opacity=0.8,
                            yaxis='y2'
                        ))
                        
                        fig.add_trace(go.Scatter(
                            x=cleaned_data['time'],
                            y=cleaned_data['extruder_current'],
                            name='挤出机电流',
                            line=dict(color='green', width=2),
                            opacity=0.8,
                            yaxis='y3'
                        ))
                        
                        fig.add_trace(go.Scatter(
                            x=cleaned_data['time'],
                            y=cleaned_data['metered_weight'],
                            name='米重',
                            line=dict(color='orange', width=2),
                            opacity=0.8,
                            yaxis='y4'
                        ))
                        
                        # 添加换料事件标记
                        for i, row in batch_changes.iterrows():
                            # 添加垂直线
                            fig.add_shape(
                                type="line",
                                x0=row['start_time'],
                                y0=0,
                                x1=row['start_time'],
                                y1=1,
                                yref="paper",
                                line=dict(color="purple", width=2, dash="dash")
                            )
                            
                            # 添加注释
                            fig.add_annotation(
                                x=row['start_time'],
                                y=1,
                                yref='paper',
                                text=f'换料: {row["compound_code"]}\n批号: {row["batch_id"]}',
                                showarrow=True,
                                arrowhead=1,
                                ax=0,
                                ay=-60
                            )
                        
                        # 配置图表布局
                        fig.update_layout(
                            title='换料操作关键参数变化趋势',
                            xaxis_title='时间',
                            xaxis=dict(
                                rangeslider=dict(visible=True),
                                type='date'
                            ),
                            yaxis_title='实际转速 (rpm)',
                            yaxis2=dict(
                                title='机头压力 (MPa)',
                                overlaying='y',
                                side='right',
                                position=0.85
                            ),
                            yaxis3=dict(
                                title='挤出机电流 (A)',
                                overlaying='y',
                                side='right',
                                position=0.92
                            ),
                            yaxis4=dict(
                                title='米重 (kg)',
                                overlaying='y',
                                side='right',
                                position=1
                            ),
                            legend=dict(
                                orientation="h",
                                yanchor="bottom",
                                y=1.02,
                                xanchor="right",
                                x=1
                            ),
                            hovermode='x unified',
                            height=700
                        )
                        
                        # 显示图表
                        st.plotly_chart(fig, width='stretch', config={'scrollZoom': True})
                        
                        # 添加数据导出功能
                        import io
                        
                        # 准备导出数据
                        export_data = []
                        for i, row in batch_changes.iterrows():
                            # 获取换料前后的数据
                            before_change = cleaned_data[cleaned_data['time'] < row['start_time']].tail(5)
                            after_change = cleaned_data[cleaned_data['time'] >= row['start_time']].head(5)
                            
                            # 添加换料事件记录
                            export_data.append({
                                'event_type': '换料事件',
                                'batch_id': row['batch_id'],
                                'compound_code': row['compound_code'],
                                'time': row['start_time'],
                                'screw_speed': '',
                                'head_pressure': '',
                                'extruder_current': '',
                                'metered_weight': ''
                            })
                            
                            # 添加换料前数据
                            for _, before_row in before_change.iterrows():
                                export_data.append({
                                    'event_type': '换料前',
                                    'batch_id': row['batch_id'],
                                    'compound_code': row['compound_code'],
                                    'time': before_row['time'],
                                    'screw_speed': before_row['screw_speed_actual'],
                                    'head_pressure': before_row['head_pressure'],
                                    'extruder_current': before_row['extruder_current'],
                                    'metered_weight': before_row['metered_weight']
                                })
                            
                            # 添加换料后数据
                            for _, after_row in after_change.iterrows():
                                export_data.append({
                                    'event_type': '换料后',
                                    'batch_id': row['batch_id'],
                                    'compound_code': row['compound_code'],
                                    'time': after_row['time'],
                                    'screw_speed': after_row['screw_speed_actual'],
                                    'head_pressure': after_row['head_pressure'],
                                    'extruder_current': after_row['extruder_current'],
                                    'metered_weight': after_row['metered_weight']
                                })
                        
                        # 转换为DataFrame
                        export_df = pd.DataFrame(export_data)
                        
                        # 创建CSV数据
                        csv_buffer = io.StringIO()
                        export_df.to_csv(csv_buffer, index=False, encoding='utf-8-sig')
                        csv_data = csv_buffer.getvalue()
                        
                        # 添加下载按钮
                        st.download_button(
                            label="下载换料操作分析数据",
                            data=csv_data,
                            file_name=f"换料操作分析_{start_date}_{end_date}.csv",
                            mime="text/csv"
                        )
                    else:
                        st.warning("未检测到换批事件，无法生成换料操作图表")
                    
                    # 显示原始数据
                    st.subheader("原始数据")
                    st.dataframe(cleaned_data, use_container_width=True)

    # 数据库连接状态
    st.sidebar.subheader("数据库状态")
    if extruder_service.db.is_connected():
        st.sidebar.success("数据库连接正常")
    else:
        st.sidebar.warning("数据库未连接")

if __name__ == "__main__":
    show_extruder_dashboard()